The AI decision layer
for analytical labs.

Scientist-trained AI that turns batch data into validated decisions and signed, explainable reports in minutes. SOP-aware and LIMS-integrated; built to scale across instruments, labs, and sites; analysts review only exceptions.

HOW IT WORKS

From batch-level decisions
to lab-wide insight

THE EI ECOSYSTEM

Two Products, One System.
EI Flow automates in-batch decisions from instrument data to signed, explainable reports.
EI Signal reveals trends across instruments, methods, and sites.

EI Flow

Make the call on every run

Automates SOP-aware decisions in minutes and sends signed reports to LIMS—analysts review only exceptions.

Explore EI Flow

EI Signal

See the lab as a system

Unifies months-to-years of data across instruments (including prep) and sites, surfacing drift and out-of-trend early with standard comparators and alerts.

Explore EI Signal

Minutes,
Not Months.

50×

Faster Reviews
Batch review cycles are significantly shortened while maintaining rigor and traceability.

High Precision,
Fewer Reruns.

Fewer Errors
Exception-only review reduces errors by removing repetitive manual decisions.

Actionable Results,

In Real Time.

10×

Faster Time to Value
Operational impact is achieved in days, not months by turning instrument data into action.

For Pharma leaders eliminating deviations, remediation, and regulatory drag in lab operations.

Built for your lab, your work.

See how EI-LSM shortens cycle time, reduces errors, and strengthens compliance

Pharma

EI speeds batch release and stability decisions with explainable outcomes and an audit-ready trail—boosting throughput without replacing the instruments and systems you trust. Analysts review only exceptions.

Food & Beverage

EI automates quality/safety calls (e.g., MOSH/MOAH, authenticity, residues) with explainable decisions and cross-site comparators—catching drift before it risks release and pushing signed results to LIMS.

Environmental

EI accelerates PFAS/pesticide/metals screening and trend monitoring across water, soil, and air—issuing explainable pass/fail and quant calls, surfacing drift early, and delivering audit-ready records to your LIMS.

Material Sciences

EI standardizes materials characterization (polymers, coatings, batteries) across spectroscopy/chromatography/imaging—flagging out-of-trend properties during stability/aging and sending signed, traceable reports to LIMS.

“EI let our scientists make faster, explainable decisions without changing our tools—now reviews take minutes and QA has an audit-ready trail.”

A smiling man with short hair against a bright red background.

John O’Mahony

ROLE?, The Coca-Cola Company

Quick answers for anyone exploring EI

FAQ

What it is, where it pays off first, and how we guide you to value.

  • Regulated analytical labs in pharma, food & beverage, environmental, and materials that need faster, safer decisions at scale. EI serves as the lab’s decision layer: EI Flow automates in-batch decisions into signed, explainable reports, while EI Signal delivers lab-wide trend insights. Both are scientist-trained, SOP-aware, LIMS-integrated and controlled by you.

  • Where batch reviews slow release or create rework. Typical wins include high-volume QC, stability checks, and authenticity or residue screening. We help pinpoint the bottleneck and quantify the lift; expect faster cycles, fewer errors, and lower cost per analysis.

  • We run a short method-selection session with your team and choose one high-volume, well-specified batch method. Examples include an LC or GC-MS quant panel, an HPLC release method, or a GC-FID authenticity check. Deliverables include acceptance criteria, data connectors, and a validation plan.

  • Phase 1: connect instruments and LIMS.
    Phase 2: configure and validate side by side against your SOP.
    Phase 3: go live with review-by-exception. Expected outcomes include minutes from batch to signed report, fewer manual errors, audit-ready records, and a clear expansion roadmap. We provide hands-on enablement and change-control templates.

  • Item desYes. EI is the decision layer that sits between instruments and LIMS or ELN. It ingests instrument output and pushes signed results to your records system. Deploy in the cloud for speed or run OnSite on your network for data residency or low latency; hybrid is supported.cription

  • Analysts stay in control. EI uses review-by-exception: routine batches auto-sign when criteria are met, and low-confidence or rule-triggered items route to humans. Your confirmations feed back to improve future calls. We train teams and tune thresholds with you.

  • EI is decision-first AI for analytical work, not a general language model. It learns from limited, instrument-level, high-quality datasets (often tens of labeled batches, with files measured in KB to low MB), applies your SOP rules, and produces explainable decisions and signed reports with version history and governance.

Can’t find the answer you’re looking for?

Set up a live demo to see EI in action end-to-end—with explainable decisions and signed, traceable reports. We’ll show how it fits your instruments & LIMS, and outline a 90-day path from first method to go-live.

REQUEST A DEMO

Bring AI
to your lab

A hands-on working session that teaches the fundamentals, maps your first high-value batch method, and ends with a personalized playbook and Pilot plan.

Level up the team: decision-first AI for analytical labs and how scientist-trained models learn from limited, instrument-level data.

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Map your first batch: define instruments, signals, acceptance criteria, and how results flow into LIMS.

A person in a red jacket walking on a dirt path through a field of flowers with mountains in the background.

Leave with a plan: a personalized AI-for-the-Lab playbook plus a 60–90 day Pilot MVP Candidate with milestones and expected outcomes.

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GET STARTED
A dashboard of data analysis showing a decision matrix with colored dots representing data points, some of which are marked as anomalies in red and orange. The left sidebar displays project information, task updates, and anomaly summaries.